Literature DB >> 17201676

Calculation of protein-ligand binding affinities.

Michael K Gilson1, Huan-Xiang Zhou.   

Abstract

Accurate methods of computing the affinity of a small molecule with a protein are needed to speed the discovery of new medications and biological probes. This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches. Important advances are reported in modeling protein-ligand energetics, such as the incorporation of electronic polarization and the use of quantum mechanical methods. Recent calculations suggest that changes in configurational entropy strongly oppose binding and must be included if accurate affinities are to be obtained. The linear interaction energy (LIE) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods are analyzed, as are free energy pathway methods, which show promise and may be ready for more extensive testing. Ultimately, major improvements in modeling accuracy will likely require advances on multiple fronts, as well as continued validation against experiment.

Mesh:

Substances:

Year:  2007        PMID: 17201676     DOI: 10.1146/annurev.biophys.36.040306.132550

Source DB:  PubMed          Journal:  Annu Rev Biophys Biomol Struct        ISSN: 1056-8700


  295 in total

1.  Conformational analysis of a polyconjugated protein-binding ligand by joint quantum chemistry and polarizable molecular mechanics. Addressing the issues of anisotropy, conjugation, polarization, and multipole transferability.

Authors:  Elodie Goldwaser; Benoit de Courcy; Luc Demange; Christiane Garbay; Françoise Raynaud; Reda Hadj-Slimane; Jean-Philip Piquemal; Nohad Gresh
Journal:  J Mol Model       Date:  2014-11-01       Impact factor: 1.810

2.  Robust scoring functions for protein-ligand interactions with quantum chemical charge models.

Authors:  Jui-Chih Wang; Jung-Hsin Lin; Chung-Ming Chen; Alex L Perryman; Arthur J Olson
Journal:  J Chem Inf Model       Date:  2011-10-07       Impact factor: 4.956

3.  Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction.

Authors:  Traian Sulea; Hervé Hogues; Enrico O Purisima
Journal:  J Comput Aided Mol Des       Date:  2011-12-25       Impact factor: 3.686

4.  Locating binding poses in protein-ligand systems using reconnaissance metadynamics.

Authors:  Pär Söderhjelm; Gareth A Tribello; Michele Parrinello
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-21       Impact factor: 11.205

5.  Putative binding modes of Ku70-SAP domain with double strand DNA: a molecular modeling study.

Authors:  Shaowen Hu; Janice M Pluth; Francis A Cucinotta
Journal:  J Mol Model       Date:  2011-09-27       Impact factor: 1.810

6.  Dynamics of thermodynamically stable, kinetically trapped, and inhibitor-bound states of pepsin.

Authors:  Derek R Dee; Brenna Myers; Rickey Y Yada
Journal:  Biophys J       Date:  2011-10-05       Impact factor: 4.033

Review 7.  Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches.

Authors:  Pierre Tuffery; Philippe Derreumaux
Journal:  J R Soc Interface       Date:  2011-10-12       Impact factor: 4.118

8.  Rapid prediction of solvation free energy. 3. Application to the SAMPL2 challenge.

Authors:  Enrico O Purisima; Christopher R Corbeil; Traian Sulea
Journal:  J Comput Aided Mol Des       Date:  2010-04-06       Impact factor: 3.686

Review 9.  Virtual screening: an endless staircase?

Authors:  Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2010-04       Impact factor: 84.694

10.  Computational delineation of tyrosyl-substrate recognition and catalytic landscapes by the epidermal growth factor receptor tyrosine kinase domain.

Authors:  Yingting Liu; Ravi Radhakrishnan
Journal:  Mol Biosyst       Date:  2014-04-29
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.